Technical Papers
Aug 5, 2019

Air Pollution and Housing Prices across Chinese Cities

Publication: Journal of Urban Planning and Development
Volume 145, Issue 4

Abstract

In recent years, China’s air pollution has drawn worldwide attention and has become a challenge for the Chinese government. Air pollution adversely impacts not only human health, but also property values. Employing the air pollution and housing price data covering 282 prefecture-level cities in China, this article confirms that air pollution has been negatively capitalized into cross-city housing prices. In addition, this article applies the local geographically weighted regression (GWR) model to unveil the spatial variation of air pollution’s capitalization effects on housing prices across different cities. Because air pollution will negatively impact housing prices, considering the benefits of air quality can help the government to create public policies intended to address air pollution, as well as help the public to improve both awareness regarding the environment and willingness to pay for improved air quality. Combing ordinary least squares (OLS) and GWR, this research serves to improve our understanding of air pollution’s capitalization effects on housing prices across Chinese cities.

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Acknowledgments

The author would like to appreciate the anonymous referees for their constructive comments. This research was supported by the National Natural Science Foundation of China (NSFC, No. 71874154) and the Special Fund for the Teaching and Research Development of Liberal Arts Faculty at Zhejiang University.

References

Aderson, R., and T. Crocker. 1971. “Air pollution and residential property values.” Urban Stud. 8 (3): 171–180. https://doi.org/10.1080/00420987120080391.
Anselin, L. 1988. Vol. 4 of Spatial econometrics: Methods and models. Norwell, MA: Kluwer Academic Publishers.
Anselin, L. 2005. Exploring spatial data with GeoDa: A workbook. Urbana, IL: Univ. of Illinois.
Anselin, L., and A. K. Bera. 1998. “Spatial dependence in linear regression models with an introduction to spatial econometrics.” In Handbook of applied economic statistics, edited by A. Ullah and D. Giles, 237–290. New York: Marcel Dekker.
Belsley, A. D., E. Kuh, and R. E. Welsch. 1980. Regression diagnostics: Identifying influential data and sources of collinearity. New York: Wiley.
Blomquist, G., M. Berger, and J. Hoen. 1988. “New estimates of quality of life in urban areas.” Am. Econ. Rev. 78 (1): 89–107.
Brunsdon, C., A. S. Fotheringham, and M. E. Charlton. 1996. “Geographically weighted regression: A method for exploring spatial nonstationarity.” Geog. Anal. 28 (4): 281–298. https://doi.org/10.1111/j.1538-4632.1996.tb00936.x.
Burnham, K. P., and D. R. Anderson. 2002. Model selection and multi-model inference: A practical information-theoretic approach. New York: Springer.
Can, A. 1992. “Specification and estimation of hedonic housing price models.” Reg. Sci. Urban Econ. 22 (3): 453–474. https://doi.org/10.1016/0166-0462(92)90039-4.
Chakraborty, J. 2009. “Automobiles, air toxics, and adverse health risks: Environmental inequities in Tampa Bay, Florida.” Ann. Assoc. Am. Geogr. 99 (4): 674–697. https://doi.org/10.1080/00045600903066490.
Chen, Y., A. Ebenstein, M. Greenstone, and H. Li. 2013. “Evidence on the impact of sustained exposure to air pollution on life expectancy from China’s Huai river policy.” Proc. Natl. Acad. Sci. U.S.A. 110 (32): 12936–12941. https://doi.org/10.1073/pnas.1300018110.
China Economic Net. 2018. “Latest data shows that China’s urbanization rate in 2017 reached 58.52%.” Accessed December 15, 2018. http://www.ce.cn/xwzx/gnsz/gdxw/201802/28/t20180228_28289397.shtml.
Costa, D. L., and M. E. Kahn. 2003. “The rising price of nonmarket goods.” Am. Econ. Rev. 93 (2): 227–232.
Dominici, F., M. Greenstone, and C. R. Sunstein. 2014. “Particulate matter matters.” Science 344 (6181): 257–259. https://doi.org/10.1126/science.1247348.
Fotheringham, A. S., C. Brunsdon, and M. Charlton. 2002. Geographically weighted regression. New York: Wiley.
Fung, Y. W., and W. L. Lee. 2014. “Development of price models for architectural and environmental quality of residential development in Hong Kong.” Habitat Int. 44 (Oct): 186–193. https://doi.org/10.1016/j.habitatint.2014.06.004.
Gilbert, A., and J. Chakraborty. 2011. “Using geographically weighted regression for environmental justice analysis: Cumulative cancer risks from air toxics in Florida.” Social Sci. Res. 40 (1): 273–286. https://doi.org/10.1016/j.ssresearch.2010.08.006.
Gorr, W. L., and A. M. Olligschlaeger. 1994. “Weighted spatial adaptive filtering: Monte Carlo studies and application to illicit drug market modeling.” Geog. Anal. 26 (1): 67–87. https://doi.org/10.1111/j.1538-4632.1994.tb00311.x.
Huang, Y., and Y. Leung. 2002. “Analysis regional industrialization in Jiangsu province using geographically weighted regression.” J. Geog. Syst. 4 (2): 233–249. https://doi.org/10.10.1007/s101090200081.
Kim, C., T. Phipps, and L. Anselin. 2003. “Measuring the benefits of air quality improvement: A spatial hedonic approach.” J. Environ. Econ. Manage. 45 (1): 24–39. https://doi.org/10.1016/S0095-0696(02)00013-X.
Leggett, C. G., and N. E. Bockstael. 2000. “Evidence of the effects of water quality on residential land prices.” J. Environ. Econ. Manage. 39 (2): 121–144. https://doi.org/10.1006/jeem.1999.1096.
Long, Y., J. Wang, K. Wu, and J. Zhang. 2014. “Population exposure to ambient PM2.5 at the subdistrict level in China. SSRN and the Beijing City Lab working paper.” Accessed October 10, 2014. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2486602.
Mennis, J. 2006. “Mapping the results of geographically weighted regression.” Cartographic J. 43 (2): 171–179. https://doi.org/10.1179/000870406X114658.
Mennis, J. L., and L. Jordan. 2005. “The distribution of environmental equity: Exploring spatial nonstationarity in multivariate models of air toxic releases.” Ann. Assoc. Am. Geog. 95 (2): 249–268. https://doi.org/10.1111/j.1467-8306.2005.00459.x.
National Bureau of Statistics of China. 2014. China city statistic yearbook of 2014. Beijing: China Statistics Press.
Partridge, M. D., D. S. Rickman, K. Ali, and M. R. Olfert. 2008. “The geographic diversity of US nonmetropolitan growth dynamics: A geographically weighted regression approach.” Land Econ. 84 (2): 241–266. https://doi.org/10.3368/le.84.2.241.
Rangel, T. F., J. A. F. Diniz-Filho, and L. M. Bini. 2010. “SAM: A comprehensive application for spatial analysis in macroecology.” Ecography 33 (1): 46–50. https://doi.org/10.1111/j.1600-0587.2009.06299.x.
Ridker, R. G., and J. A. Henning. 1967. “The determinants of residential property values with special reference to air pollution.” Rev. Econ. Stat. 49 (2): 246–257. https://doi.org/10.2307/1928231.
Rosen, S. 1974. “Hedonic prices and implicit markets.” J. Political Economy 82 (1): 34–35.
Rosen, S. 2002. “Markets and diversity.” Am. Econ. Rev. 92 (1): 1–15. https://doi.org/10.1257/000282802760015577.
Smith, V. K., and J. C. Huang. 1993. “Hedonic models and air pollution: Twenty-five years and counting.” Environ. Resour. Econ. 3 (4): 381–394. https://doi.org/10.1007/BF00418818.
Sun, C., M. E. Kahn, and S. Zheng. 2017. “Self-protection investment exacerbates air pollution exposure inequality in urban China.” Ecol. Econ. 131 (Jan): 468–474. https://doi.org/10.1016/j.ecolecon.2016.06.030.
SWUFE and PBC (Southwestern University of Finance and Economics and People’s Bank of China). 2012. The report of family financial investment of China. Chengdu: Southwestern Univ. of Finance and Economics Press.
The United Nations. 2013. “China national human development report 2013.” Accessed February 05, 2014. http://www.cn.undp.org/content/dam/china/docs/Publications/UNDP-CH_2013%20NHDR_EN.pdf.
Wheeler, D. C. 2007. “Diagnostic tools and a remedial method for collinearity in geographically weighted regression.” Environ Plann. A 39 (10): 2464–2481. https://doi.org/10.1068/a38325.
World Bank. 2007. Cost of pollution in China: Economic estimates of physical damage. Washington, DC: World Bank.
Yu, D. 2007. “Modeling owner-occupied single-family house values in the city of Milwaukee: A geographically weighted regression approach.” GIScience Remote Sens. 44 (3): 267–282. https://doi.org/10.2747/1548-1603.44.3.267.
Yu, D., Y. Wei, and C. Wu. 2007. “Modeling spatial dimensions of housing prices in Milwaukee, WI.” Environ. Plann. B 34 (6): 1085–1102. https://doi.org/10.1068/b32119.
Yu, X., and D. Abler. 2010. “Incorporating zero and missing responses into CVM with open-ended bidding: Willingness to pay for blue skies in Beijing.” Environ. Dev. Econ. 15 (5): 535–556. https://doi.org/10.1017/S1355770X10000197.
Zabel, J. E., and K. A. Kiel. 2000. “Estimating the demand for air quality in four US cities.” Land Econ. 76 (2): 174–194. https://doi.org/10.2307/3147223.
Zhang, A., Q. Qi, L. Jiang, F. Zhou, and J. Wang. 2013. “Population exposure to PM2.5 in the urban area of Beijing.” PLoS One 8 (5): e63486. https://doi.org/10.1371/journal.pone.0063486.
Zhang, H., J. Zhang, S. Lu, S. Cheng, and J. Zhang. 2011. “Modeling hotel room price with geographically weighted regression.” Int. J. Hospitality Manage. 30 (4): 1036–1043. https://doi.org/10.1016/j.ijhm.2011.03.010.
Zhang, Q., K. He, and H. Huo. 2012. “Policy: Cleaning China’s air.” Nature 484 (7393): 161–162. https://doi.org/10.1038/484161a.
Zheng, S., J. Cao, M. E. Kahn, and C. Sun. 2014. “Real estate valuation and cross-boundary air pollution externalities: Evidence from Chinese cities.” J. Real Estate Finance Econ. 48 (3): 398–414. https://doi.org/10.1007/s11146-013-9405-4.
Zheng, S., M. E. Kahn, and H. Liu. 2010. “Towards a system of open cities in China: Home prices, FDI flows and air quality in 35 major cities.” Reg. Sci. Urban Econ. 40 (1): 1–10. https://doi.org/10.1016/j.regsciurbeco.2009.10.003.
Zhong, R., W. Zhao, Y. Zou, and R. J. Mason. 2018. “University campuses and housing markets: Evidence from Nanjing.” Prof. Geog. 70 (2): 175–185. https://doi.org/10.1080/00330124.2017.1325750.
Zou, Y. 2015a. “Re-examining the neighborhood distribution of higher priced mortgage lending: Global versus local methods.” Growth Change 46 (4): 654–674. https://doi.org/10.1111/grow.12121.
Zou, Y. 2015b. “Subprime mortgages and housing price variations in the Philadelphia metropolitan area.” Prof. Geog. 67 (3): 412–426. https://doi.org/10.1080/00330124.2014.987198.

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Journal of Urban Planning and Development
Volume 145Issue 4December 2019

History

Received: Jul 14, 2017
Accepted: Feb 13, 2019
Published online: Aug 5, 2019
Published in print: Dec 1, 2019
Discussion open until: Jan 5, 2020

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Yonghua Zou, Ph.D. [email protected]
ZJU 100 Young Professor, School of Public Affairs, Zhejiang Univ., Hangzhou 310058, PR China. Email: [email protected]

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